Choosing arrival process models for service systems: Tests of a nonhomogeneous Poisson process

Service systems such as call centers and hospital emergency rooms typically have strongly time‐varying arrival rates. Thus, a nonhomogeneous Poisson process (NHPP) is a natural model for the arrival process in a queueing model for performance analysis. Nevertheless, it is important to perform statistical tests with service system data to confirm that an NHPP is actually appropriate, as emphasized by Brown et al. [8]. They suggested a specific statistical test based on the Kolmogorov–Smirnov (KS) statistic after exploiting the conditional‐uniform (CU) property to transform the NHPP into a sequence of i.i.d. random variables uniformly distributed on [0,1] and then performing a logarithmic transformation of the data. We investigate why it is important to perform the final data transformation and consider what form it should take. We conduct extensive simulation experiments to study the power of these alternative statistical tests. We conclude that the general approach of Brown et al. [8] is excellent, but that an alternative data transformation proposed by Lewis [22], drawing upon Durbin [10], produces a test of an NHPP test with consistently greater power. We also conclude that the KS test after the CU transformation, without any additional data transformation, tends to be best to test against alternative hypotheses that primarily differ from an NHPP only through stochastic and time dependence. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 66–90, 2014     

测量TOA和DOA的单站无源定位跟踪可观测条件

单站无源定位跟踪技术中,可观测性分析是一个关键问题,但是由于TOA测量方程的非线性程度太高,直接通过计算Jacobin矩阵得到的可观测矩阵形式非常复杂,很难得出明确的分析结果。采用新的思路推导了一种TOA测量方程的线性化方程,分析了测量TOA和DOA单站无源定位的可观测条件。最后给出了计算机仿真结果。     

基于多目标的雷达组网传感器资源管理算法

在雷达组网系统的多目标跟踪过程中,当目标数量过多时,由于传感器资源不足,无法使用传统传感器的管理方法进行资源分配,且运算时间过长,不满足工程实际需求。针对以上问题,提出了一种新的多传感器多目标跟踪任务快速分配算法,该算法将跟踪目标个数和跟踪目标精度作为优化目标,首先按照设定的分配准则对传感器进行一次分配,最大化跟踪目标个数;然后利用一种基于传感器排序的启发式传感器分配方法进行二次分配,通过控制跟踪目标的协方差水平,使目标的跟踪精度尽量接近期望值。仿真结果表明,该算法能够在较短的时间内对多传感器进行有效快速地分配,既跟踪了更多的目标,又达到了期望目标的跟踪精度,并且在一定程度上控制资源消耗,减少系统的总耗能。     

LFM脉冲雷达距离维快速搜索处理算法

针对脉冲雷达近距离目标遮挡问题,从理论上分析了雷达最小作用距离不受限于脉冲宽度.在此基础上,以Chirp脉冲为例,提出了一种适合远近距离全程目标的快速搜索处理算法.该算法只需发射一种宽脉冲波形,而不必根据距离的变化改变脉宽,从而有效缩短了搜索时间,大大提高了搜索效率.仿真结果表明了理论分析的正确性和算法的有效性.     

网络入侵检测的快速规则匹配算法

在分析入侵检测系统的基础上,指出现有规则匹配算法的不足.提出一种新的规则匹配算法,该算法主要利用非精确匹配技术,缩小入侵分类的检测范围,达到快速匹配的目的.根据不同的安全性要求设置不同的门限值,该算法可用于预测适合不同门限值的可疑入侵行为.     

基于方位角变化率的快速高精度无源定位方法

在分析现有单站无源定位方法优缺点的基础上,根据运动平台对固定目标无源定位技术的特点,提出了一种通过方位角变化率信息对观测站与目标间距离进行解算的快速高精度无源定位方法。并通过仿真,验证了该方法是一种高精度、快速的定位方法,具有较强的通用性。其主要应用于机载无源探测设备对地面固定雷达站或其他辐射源定位,从而为引导导弹对其攻击提供必要的数据。     

外辐射源雷达系统中时延估计算法及仿真

时延估计的方法有经典的广义相关法、自适应法、循环平稳法、高阶累积量法、时频分析法等,重点分析了外辐射源雷达系统中用于时延估计的循环平稳法和相关法,并给出了循环平稳法和相关法用于时延估计的仿真,得出了仿真结果。仿真结果表明,对QPSK信号无法用循环平稳的方法来进行时差的获取,用相关法在极低信噪比条件下检测出目标信号,长时间的信号积累是必需的。     

分布式到达时间控制器装备维修任务实时调度方法

战时装备维修企业的生产环境呈现出更多的不确定性,合理安排维修任务来适应这种不确定性使实际修复时间与计划时间偏差最小是什么重要的.为此,提出了一种面向准时制造的实时生产调度方法,这种生产调度系统有多个独立的智能体,每个智能体通过到达时间控制器和仿真系统的反馈来调整对应维修任务的到达时间,然后通过先来先服务的调度规则确认维...     

Using stochastic programming to solve an outpatient appointment scheduling problem with random service and arrival times

We study a stochastic outpatient appointment scheduling problem (SOASP) in which we need to design a schedule and an adaptive rescheduling (i.e., resequencing or declining) policy for a set of patients. Each patient has a known type and associated probability distributions of random service duration and random arrival time. Finding a provably optimal solution to this problem requires solving a multistage stochastic mixed‐integer program (MSMIP) with a schedule optimization problem solved at each stage, determining the optimal rescheduling policy over the various random service durations and arrival times. In recognition that this MSMIP is intractable, we first consider a two‐stage model (TSM) that relaxes the nonanticipativity constraints of MSMIP and so yields a lower bound. Second, we derive a set of valid inequalities to strengthen and improve the solvability of the TSM formulation. Third, we obtain an upper bound for the MSMIP by solving the TSM under the feasible (and easily implementable) appointment order (AO) policy, which requires that patients are served in the order of their scheduled appointments, independent of their actual arrival times. Fourth, we propose a Monte Carlo approach to evaluate the relative gap between the MSMIP upper and lower bounds. Finally, in a series of numerical experiments, we show that these two bounds are very close in a wide range of SOASP instances, demonstrating the near‐optimality of the AO policy. We also identify parameter settings that result in a large gap in between these two bounds. Accordingly, we propose an alternative policy based on neighbor‐swapping. We demonstrate that this alternative policy leads to a much tighter upper bound and significantly shrinks the gap.     

数字化扩频接收机的自适应抗干扰滤波方案研究

讨论了自适应抗干扰滤波在最小频移键控的直接序列扩频(DS-MSK)数字化接收机中的应用问题,对非线性滤波加以改进,提出了部分解扩非线性滤波(PDNF)结构,将快速更新子带自适应滤波(FRSAF)算法用于PDNF结构以提高收敛速度。结合FRSAF算法的PDNF自适应抗干扰滤波方案在收敛速度、稳健性和输出信噪比等方面明显优于结合LMS算法的传统非线性抗干扰滤波方案,仿真结果验证了上述结论。